Yihua Zhang
Room 3210
428 S Shaw LN
East Lansing, Michigan
United States of America
I am Yihua Zhang (张逸骅), a third-year Ph.D. student from OPTML Group at Michigan State University, supervised by Prof. Sijia Liu. My research focuses on the trustworthy and scalable ML algorithms. In general, my research spans the areas of machine learning (ML)/deep learning (DL), optimization theory, computer vision, and security. These research topics provide a solid foundation for my current and future research: Making AI system responsible and efficient. My research on these two goals are intervened and can be summarized as the following two perspectives:
Algorithmic perspective: This line of research designs the scalable and theoretically-grounded machine learning algorithms subject to real-life constraints, including bi-level optimization, zeroth-order optimization, inviriant risk minimization, etc.
Application perspective: This line of research tackles the domain-specific challenges to achieve scalable and trustworthy AI, including data and model pruning, efficient model structures, model robustness and unlearning, etc.
News
Sep 26, 2024 | One first-authored paper (UnlearnCanvas) accepted in NeurIPS 2024 Dataset & Benchmark Track! |
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Sep 25, 2024 | Two papers accepted in NeurIPS 2024! |
Sep 19, 2024 | One paper accepted in EMNLP 2024! See our paper and code here! |
Aug 28, 2024 | I will start working as a research scientist intern at Meta AI! |
Jul 1, 2024 | One paper accepted by ECCV’24! |